A hybrid machine learning/pharmacokinetic approach outperforms maximum a posteriori Bayesian estimation by selectively flattening model priors

• Huvudskapare: Jasmine H. Hughes (Författare, medförfattare), Ron J. Keizer (Författare, medförfattare)
• Materialtyp: Bok
• Publicerad: Wiley, 2021-10-01T00:00:00Z.
• Ämnen: article
• Länkar: Connect to this object online.

Abstract Model‐informed precision dosing (MIPD) approaches typically apply maximum a posteriori (MAP) Bayesian estimation to determine individual pharmacokinetic (PK) parameters with the goal of optimizing future dosing regimens. This process combines knowledge about the individual, in the form of d...